Basic Regression Analysis EViews has a very powerful and easy-to-use estimation toolkit that allows you to estimate from the simplest to the most complex regression analysis . This tutorial explains basic regression techniques in EViews for single equation regressions using cross-section data. The main topics include: Specifying and estimating an equation Equation Objects (saving, labeling, freezing, printing) Equation Output: Analyzing and Interpreting results Multiple Regression Analysis Estimation with Data Expressions and Functions Post Estimation: Working with Equations Hypothesis testing Estimation Options (robust standard errors, weighted least squares) 2
Estimation: the Basics Note: Information for examples in this portion of tutorial: Data: Tutorial12_data.xls Results: Tutorial12_results.wf1 Practice Workfile: Tutorial12.wf1
Description of Data File Data_wf1 has the following data on 9,275 individuals* Wealth – net total financial wealth (in thousands of dollars) Income – annual income (in thousands of dollars) Male – dummy variable, equal to 1 if male, 0 otherwise Married – dummy variable, equal to 1 if married, 0 otherwise Age – age in years (minimum age in the dataset is 25 years). Fsize – family size; number of individuals living in the family. 4 * This data is from Wooldridge, Introductory Econometrics (4 th Edition).
Equation Object: Specification and Estimation
The Equation Object Single equation regression estimation in EViews is performed using the Equation Object. There are a number of ways to create a simple OLS Equation Object: 6 From the Main menu, select Object → New Object → Equation. From the Main menu, select Quick → Estimate Equation. On the command window type: ls
The Equation Box In all cases, the Equation Estimation box appears. You need to specify three things in this dialogue box: The equation specification. The estimation method. The sample. 7 Specify your equation either by: List Formula (explained in future tutorials) Specify your estimation method Specify your sample
Specifying an Equation by List The easiest way to specify a linear equation is to provide a list of variables that you wish to use in the equation. 8 Suppose that you would like to know how well income explains financial wealth . To accomplish this, type in the Equation Estimation box The dependent variable ( wealth ). “c” for constant. The independent variable ( income ). Notice that all the entries are all separated by spaces.
Specifying Equation by List (cont’d) Alternatively, you can also create an Equation simply by selecting the series and opening them as Equation. 9 To create an equation: Select wealth and income by clicking on these series in the workfile (press CTRL to select multiple series). Notice that you need to select the dependent variable ( wealth ) first. Right click and select Open → as Equation.
Specifying Equation by List (cont’d) The Equation Estimation dialog box opens, listing your independent, dependent variables, and the constant. Click OK to estimate regression. 10
Estimation Method After you specify the variable list, you need to select an estimation method. Click on the Method option, and you see a drop-down menu listing the various estimation method you can perform in EViews. Standard, single equation regression, is performed using “Least Squares” (LS). In this tutorial we will use Least Squares and defer discussion of more advanced estimation techniques in subsequent tutorials. 11
Estimation Sample The third item you need to specify in the equation box is the Sample . You can specify the sample period in the sample space of the equation box . For example, to estimate the following regression over the entire sample: You need to include all observations (1 to 9275). Click OK to estimate the regression. As seen in Equation Output, EViews has included all observations when estimating this regression. 12
Estimation Sample (cont’d) What if you want to estimate the effect of income on wealth, but only for a subset of individuals, e.g., married men? To target a specific sample you need to: Specify the sample: in this case male and married so type: if married=1 and male=1 . Click OK to estimate the regression. As seen in Equation Output, EViews has included only a subset of total observations (534 obs. ) 13